Centre for Fisheries Ecosystems Research, Fisheries & Marine Institute, Memorial University, St. John's, Newfoundland and Labrador, Canada.
Spanish Institute of Oceanography (IEO, CSIC), Madrid Oceanographic Center, Madrid, Spain.
PLoS One. 2024 Apr 1;19(4):e0300311. doi: 10.1371/journal.pone.0300311. eCollection 2024.
Canadian fisheries management has embraced the precautionary approach and the incorporation of ecosystem information into decision-making processes. Accurate estimation of fish stock biomass is crucial for ensuring sustainable exploitation of marine resources. Spatio-temporal models can provide improved indices of biomass as they capture spatial and temporal correlations in data and can account for environmental factors influencing biomass distributions. In this study, we developed a spatio-temporal generalized additive model (st-GAM) to investigate the relationships between bottom temperature, depth, and the biomass of three key fished species on The Grand Banks: snow crab (Chionoecetes opilio), yellowtail flounder (Limanda ferruginea), and Atlantic cod (Gadus morhua). Our findings revealed changes in the centre of gravity of Atlantic cod that could be related to a northern shift of the species within the Grand Banks or to a faster recovery of the 2J3KL stock. Atlantic cod also displayed hyperaggregation behaviour with the species showing a continuous distribution over the Grand Banks when biomass is high. These findings suggest a joint stock assessment between the 2J3KL and 3NO stocks would be advisable. However, barriers may need to be addressed to achieve collaboration between the two distinct regulatory bodies (i.e., DFO and NAFO) in charge of managing the stocks. Snow crab and yellowtail flounder centres of gravity have remained relatively constant over time. We also estimated novel indices of biomass, informed by environmental factors. Our study represents a step towards ecosystem-based fisheries management for the highly dynamic Grand Banks.
加拿大渔业管理部门采用了预防性方法,并将生态系统信息纳入决策过程。准确估计鱼类种群生物量对于确保海洋资源的可持续开发至关重要。时空模型可以提供改进的生物量指数,因为它们可以捕捉数据中的空间和时间相关性,并可以解释影响生物量分布的环境因素。在本研究中,我们开发了一种时空广义加性模型(st-GAM),以研究大浅滩上三种主要捕捞物种(雪蟹(Chionoecetes opilio)、黄尾鲽(Limanda ferruginea)和大西洋鳕鱼(Gadus morhua))的底部温度、深度和生物量之间的关系。我们的研究结果揭示了大西洋鳕鱼重心的变化,这可能与该物种在大浅滩内的北移有关,也可能与 2J3KL 种群的更快恢复有关。大西洋鳕鱼还表现出超聚集行为,当生物量较高时,该物种在大浅滩上呈连续分布。这些发现表明,建议对 2J3KL 和 3NO 种群进行联合评估。然而,为了实现负责管理这些种群的两个不同监管机构(即 DFO 和 NAFO)之间的合作,可能需要解决障碍。雪蟹和黄尾鲽的重心在时间上相对保持不变。我们还根据环境因素估计了新的生物量指数。我们的研究代表了朝着基于生态系统的渔业管理方向迈出的一步,以应对高度动态的大浅滩。